Machine learning in drug discovery

Machine learning in drug discovery uses algorithms to analyze vast amounts of biological and chemical data. These algorithms identify patterns and relationships that might be difficult for humans to detect, helping researchers predict how different compounds will interact with targets in the body. This accelerates the process of finding promising drug candidates, reduces costs, and improves accuracy. Essentially, machine learning acts as a powerful tool that learns from data to guide scientists in designing and testing new drugs more efficiently and effectively.